Solving the long-range dependency problem

We have seen in the previous section that it is difficult for vanilla RNNs to effectively learn long-range dependencies due to vanishing and exploding gradients. To address this issue, Long Short Term Memory network was developed in 1997 by Sepp Hochreiter and Jürgen Schmidhuber. Gated Recurrent Unit was introduced in 2014 and gives a simpler version of LSTM. Let's review how LSTM and GRU solve the problem of learning long-range dependencies.

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